Abstract
Formation of an effective project team plays an important role in successful completion of the projects in organizations. As the computation involved in this task grows exponentially with the growth in the size of personnel, manual implementation is of no use. Decision support systems (DSS) developed by specialized consultants help large organizations in personnel selection process. Since, the given problem can be modelled as a combinatorial optimization problem, Genetic Algorithmic approach is preferred in building the decision making software. Fuzzy descriptors are being used to facilitate the flexible requirement specifications that indicates required team member skills. The Quantum Walk based Genetic Algorithm (QWGA) is proposed in this paper to identify near optimal teams that optimizes the fuzzy criteria obtained from the initial team requirements. Efficiency of the proposed design is tested on a variety of artificially constructed instances. The results prove that the proposed optimization algorithm is practical and effective.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Intelligent Information Technologies
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
